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  1. 1
    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image

    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2014
    “…This algorithm provides a decision tree output to represent the knowledge model, enabled a faster classification of intra-urban classes, and disabled the subjectivities which are related to the interaction of the analyst. …”
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  2. 2
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…A large number of attributes were discovered with the C4.5 DM algorithm, which also generated the classification model as a decision tree. …”
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  3. 3
    Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image

    Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image by Shojanoori, Razieh

    Published 2016
    “…In this research, most of satisfactory results achieved from the generic model and proves it can be easily performed to different WorldView-2 images from different areas and provided the high accuracy through algorithms for tree species detection namely, Mesua Ferrea, Samanea Saman, and Casuarina Sumatrana without using any training data. …”
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  4. 4
    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…Features are then enhanced by using Tree-based feature selection to reduce the size of each feature and, therefore, enhance classification performance. …”
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  5. 5
    The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification

    The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification by Mokhairi, Makhtar, Engku Fadzli Hasan, Syed Abdullah, Fatma Susilawati, Mohamad

    Published 2015
    “…With the explosive growth of methods in this research area, this paper proposes 5 processing steps before image annotation using Amazon dataset, i.e., image segmentation, object identification, feature extraction, feature selection and image features classification. …”
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  6. 6
    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…On the other hand, BrT classification is aimed to develop an efficient and reliable model namely Biopsy Microscopic Image Cancer Network (BMIC-Net) to classify Hp images into eight subtypes of BrT through a DL-based hierarchical classification approach. …”
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  7. 7
    Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing

    Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing by Hamedianfar, Alireza

    Published 2015
    “…This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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  8. 8
    Imaging spectroscopy and light detection and ranging data fusion for urban features extraction

    Imaging spectroscopy and light detection and ranging data fusion for urban features extraction by Idrees, Mohammed, Mohd Shafri, Helmi Zulhaidi, Saeidi, Vahideh

    Published 2013
    “…The composite image was classified using unsupervised classification (k-mean algorithm) and the accuracy of the classification assessed. …”
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  9. 9
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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  10. 10
    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation

    Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation by Pande C.B., Srivastava A., Moharir K.N., Radwan N., Mohd Sidek L., Alshehri F., Pal S.C., Tolche A.D., Zhran M.

    Published 2025
    “…A novel multiple composite RF approach based on LULC classification was utilized to generate the final LULC classification maps utilizing the RF-50 and RF-100 tree models. …”
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  11. 11
    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi

    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

    Published 2022
    “…While the best predicted selection using RF is model 4 with mtry = p produced R2= 0.997 and RMSE=30.653kg/tree. …”
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  12. 12
    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri

    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

    Published 2023
    “…The best performance obtained using Savitzky-Golay smoothing and LDA algorithms after the wavelength selection with the accuracy reported of 0.90. …”
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  13. 13
    Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine

    Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine by Molla Salilew, W., Ambri Abdul Karim, Z., Alemu Lemma, T.

    Published 2022
    “…Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. …”
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  14. 14
    Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine

    Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine by Molla Salilew, W., Ambri Abdul Karim, Z., Alemu Lemma, T.

    Published 2022
    “…Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. …”
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  15. 15
    Mixed waste classification based on vision inspection / Hassan Mehmood Khan

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
    “…The best 17 resulting features were used for the next process. Four classification algorithms specifically the Cubic SVM (C.SVM), Quadratic SVM (Q.SVM), Ensemble Bagged Trees (EBT) and k-Nearest Neighbor (kNN) are employed to test the classification accuracy. …”
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  16. 16
    Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging

    Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

    Published 2022
    “…Several machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, support vector machine, decision tree, and Naïve Bayes were applied for the classification of pineapple varieties. …”
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  17. 17
    Optimized techniques for landslide detection and characteristics using LiDAR data

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. …”
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  18. 18
    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza

    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

    Published 2024
    “…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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  19. 19
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. …”
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  20. 20
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
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